Journal Description
Diagnostics
Diagnostics
is an international, peer-reviewed, open access journal on medical diagnosis published semimonthly online by MDPI. The British Neuro-Oncology Society (BNOS), the International Society for Infectious Diseases in Obstetrics and Gynaecology (ISIDOG) and the Swiss Union of Laboratory Medicine (SULM) are affiliated with Diagnostics and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Embase, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q1 (Medicine, General and Internal) / CiteScore - Q2 (Internal Medicine)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.5 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journal: LabMed.
Impact Factor:
3.0 (2023);
5-Year Impact Factor:
3.1 (2023)
Latest Articles
Echocardiography in Cardiac Arrest: Incremental Diagnostic and Prognostic Role during Resuscitation Care
Diagnostics 2024, 14(18), 2107; https://doi.org/10.3390/diagnostics14182107 (registering DOI) - 23 Sep 2024
Abstract
Background: Cardiac arrest (CA) is a life-critical condition. Patients who survive after CA go into a defined post-cardiac arrest syndrome (PCAS). In this clinical context, the role of the echocardiogram in recent years has become increasingly important to assess the causes of arrest,
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Background: Cardiac arrest (CA) is a life-critical condition. Patients who survive after CA go into a defined post-cardiac arrest syndrome (PCAS). In this clinical context, the role of the echocardiogram in recent years has become increasingly important to assess the causes of arrest, the prognosis, and any direct and indirect complications dependent on cardiopulmonary resuscitation (CPR) maneu-vers. Methods: We have conduct a narrative revision of literature. Results: The aim of our review is to evaluate the increasingly important role of the transthoracic and transesophageal echocardiogram in the CA phase and especially post-arrest, analyzing the data already present in the literature. Conclusion: Transthoracic and transesophageal echocardiogram in the CA phase take on important diagnostic and prognostic role.
Full article
(This article belongs to the Special Issue Recent Advances in Echocardiography)
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Open AccessBrief Report
Radiofrequency Echographic Multi Spectrometry (REMS) Technology for Bone Health Status Evaluation in Kidney Transplant Recipients
by
Angelo Fassio, Giovanni Adami, Stefano Andreola, Pietro Manuel Ferraro, Paola Pisani, Fiorella Anna Lombardi, Ombretta Viapiana, Maurizio Rossini, Chiara Caletti, Giovanni Gambaro, Matteo Gatti and Davide Gatti
Diagnostics 2024, 14(18), 2106; https://doi.org/10.3390/diagnostics14182106 (registering DOI) - 23 Sep 2024
Abstract
Background: A significant loss in bone density and strength occurs during the post-renal-transplant period with higher susceptibility to fracture. The study aims to compare the performance of the Radiofrequency Echographic Multi Spectrometry (REMS) in the bone mineral density assessment with the conventional
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Background: A significant loss in bone density and strength occurs during the post-renal-transplant period with higher susceptibility to fracture. The study aims to compare the performance of the Radiofrequency Echographic Multi Spectrometry (REMS) in the bone mineral density assessment with the conventional dual-energy X-ray absorptiometry (DXA) in a cohort of kidney transplant recipients (KTR). Methods: A cohort of 40 patients underwent both DXA and REMS examinations on the lumbar spine and/or proximal femur. The paired t-test was used to compare DXA and REMS measurements; the chi-square test was used to compare the prevalence of osteoporosis/osteopenia. The agreement between the two techniques was assessed through Spearman’s correlation. Results: As expected, most KTR patients were osteopenic or osteoporotic with both REMS and DXA (86.5% and 81% for the femur; 88% and 65% for the lumbar spine p < 0.05). A modest correlation (r = 0.4, p < 0.01) was observed at the lumbar spine between the T-score measured by REMS and DXA. A strong correlation was defined between REMS and DXA in the femoral region (r = 0.7, p < 0.0001). Conclusions: The study demonstrates the exchangeability of the two techniques on the proximal femur in KTR and a higher diagnostic accuracy of REMS at the spine level than DXA.
Full article
(This article belongs to the Section Biomedical Optics)
Open AccessReview
Imaging in Renal Cell Carcinoma Detection
by
Dixon Woon, Shane Qin, Abdullah Al-Khanaty, Marlon Perera and Nathan Lawrentschuk
Diagnostics 2024, 14(18), 2105; https://doi.org/10.3390/diagnostics14182105 (registering DOI) - 23 Sep 2024
Abstract
Introduction: Imaging in renal cell carcinoma (RCC) is a constantly evolving landscape. The incidence of RCC has been rising over the years with the improvement in image quality and sensitivity in imaging modalities resulting in “incidentalomas” being detected. We aim to explore the
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Introduction: Imaging in renal cell carcinoma (RCC) is a constantly evolving landscape. The incidence of RCC has been rising over the years with the improvement in image quality and sensitivity in imaging modalities resulting in “incidentalomas” being detected. We aim to explore the latest advances in imaging for RCC. Methods: A literature search was conducted using Medline and Google Scholar, up to May 2024. For each subsection of the manuscript, a separate search was performed using a combination of the following key terms “renal cell carcinoma”, “renal mass”, “ultrasound”, “computed tomography”, “magnetic resonance imaging”, “18F-Fluorodeoxyglucose PET/CT”, “prostate-specific membrane antigen PET/CT”, “technetium-99m sestamibi SPECT/CT”, “carbonic anhydrase IX”, “girentuximab”, and “radiomics”. Studies that were not in English were excluded. The reference lists of selected manuscripts were checked manually for eligible articles. Results: The main imaging modalities for RCC currently are ultrasound, computed tomography (CT) and magnetic resonance imaging (MRI). Contrast-enhanced US (CEUS) has emerged as an alternative to CT or MRI for the characterisation of renal masses. Furthermore, there has been significant research in molecular imaging in recent years, including FDG PET, PSMA PET/CT, 99mTc-Sestamibi, and anti-carbonic anhydrase IX monoclonal antibodies/peptides. Radiomics and the use of AI in radiology is a growing area of interest. Conclusions: There will be significant change in the field of imaging in RCC as molecular imaging becomes increasingly popular, which reflects a shift in management to a more conservative approach, especially for small renal masses (SRMs). There is the hope that the improvement in imaging will result in less unnecessary invasive surgeries or biopsies being performed for benign or indolent renal lesions.
Full article
(This article belongs to the Special Issue Kidney Disease: Biomarkers, Diagnosis, and Prognosis: 3rd Edition)
Open AccessReview
[18F]FDG PET/CT Integration in Evaluating Immunotherapy for Lung Cancer: A Clinician’s Practical Approach
by
Juliette Brezun, Nicolas Aide, Evelyne Peroux, Jean-Laurent Lamboley, Fabrice Gutman, David Lussato and Carole Helissey
Diagnostics 2024, 14(18), 2104; https://doi.org/10.3390/diagnostics14182104 (registering DOI) - 23 Sep 2024
Abstract
The advent of immune checkpoint inhibitors (ICIs) has revolutionized the treatment paradigm of lung cancer, resulting in notable enhancements in patient survival. Nevertheless, evaluating treatment response in patients undergoing immunotherapy poses distinct challenges due to unconventional response patterns like pseudoprogressive disease (PPD), dissociated
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The advent of immune checkpoint inhibitors (ICIs) has revolutionized the treatment paradigm of lung cancer, resulting in notable enhancements in patient survival. Nevertheless, evaluating treatment response in patients undergoing immunotherapy poses distinct challenges due to unconventional response patterns like pseudoprogressive disease (PPD), dissociated response (DR), and hyperprogressive disease (HPD). Conventional response criteria such as the RECIST 1.1 may not adequately address these complexities. To tackle this issue, novel response criteria such as the iRECIST and imRECIST have been proposed, enabling a more comprehensive assessment of treatment response by incorporating additional scans and considering the best overall response even after radiologic progressive disease evaluation. Additionally, [18F]FDG PET/CT imaging has emerged as a valuable modality for evaluating treatment response, with various metabolic response criteria such as the PERCIMT, imPERCIST, and iPERCIST developed to overcome the limitations of traditional criteria, particularly in detecting pseudoprogression. A multidisciplinary approach involving oncologists, radiologists, and nuclear medicine specialists is crucial for effectively navigating these complexities and enhancing patient outcomes in the era of immunotherapy for lung cancer. In this review, we delineate the key components of these guidelines, summarizing essential aspects for radiologists and nuclear medicine physicians. Furthermore, we provide insights into how imaging can guide the management of individual lung cancer patients in real-world multidisciplinary settings.
Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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Open AccessArticle
Age Estimation through Hounsfield Unit Analysis of Pelvic Bone in the Romanian Population
by
Emanuela Stan, Alexandra Enache, Camelia-Oana Muresan, Veronica Ciocan, Stefania Ungureanu, Alexandru Catalin Motofelea, Adrian Voicu and Dan Costachescu
Diagnostics 2024, 14(18), 2103; https://doi.org/10.3390/diagnostics14182103 (registering DOI) - 23 Sep 2024
Abstract
Background: Bone density is affected by age- and sex-related changes in the os coxae, often known as the pelvic bone. Recent developments in computed tomography (CT) imaging have created new opportunities for quantitative analysis, notably regarding Hounsfield Units (HU). Objectives: The study aims
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Background: Bone density is affected by age- and sex-related changes in the os coxae, often known as the pelvic bone. Recent developments in computed tomography (CT) imaging have created new opportunities for quantitative analysis, notably regarding Hounsfield Units (HU). Objectives: The study aims to investigate the possibility of using HU obtained from os coxae CT scans to estimate age in the Romanian population. Methods: A statistical analysis was conducted on a sample of 80 pelvic CT scans in order to find any significant correlation between age, sex, and variation in density among the different pelvic bone locations of interest. According to the research, pelvic radiodensity measurements varied significantly between male and female participants, with men having greater levels. This technique may be valuable for determining an individual’s sex precisely, as evidenced by the substantial association found between HU levels and changes in bone density associated with sex. Results: The analysis of variance underscores that HU values exhibit a significant negative relationship with radiodensity, with a general trend of decreasing HU with increasing age. The equation derived from the ordinary least squares OLS regression analysis can be used to estimate the age of individuals in the Romanian population based on their HU values at specific pelvic sites. Conclusions: In conclusion, the application of HU analysis in CT imaging of the coxae represents a non-invasive and potentially reliable method for age and sex estimation, and a promising avenue in the field of human identification.
Full article
(This article belongs to the Special Issue Advances in Forensic Medical Diagnosis)
Open AccessArticle
Insights into the Neutrophil-to-Lymphocyte Ratio and the Platelet-to-Lymphocyte Ratio as Predictors for the Length of Stay and Readmission in Chronic Heart Failure Patients
by
Liviu Cristescu, Ioan Tilea, Dragos-Gabriel Iancu, Florin Stoica, Diana-Andreea Moldovan, Vincenzo Capriglione and Andreea Varga
Diagnostics 2024, 14(18), 2102; https://doi.org/10.3390/diagnostics14182102 (registering DOI) - 23 Sep 2024
Abstract
Background/Objectives: Chronic heart failure (CHF) is characterized by complex pathophysiology, leading to increased hospitalizations and mortality. Inflammatory biomarkers such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) provide valuable diagnostic insights. Methods: This study evaluates the prognostic relationship between NLR, PLR, and,
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Background/Objectives: Chronic heart failure (CHF) is characterized by complex pathophysiology, leading to increased hospitalizations and mortality. Inflammatory biomarkers such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) provide valuable diagnostic insights. Methods: This study evaluates the prognostic relationship between NLR, PLR, and, in a specific subcohort, N-terminal pro B-type natriuretic peptide (NT-proBNP), alongside length of stay (LOS) and 90-day readmission rates in CHF patients, irrespective of heart failure phenotype. A retrospective analysis of 427 CHF admissions (males = 57.84%) was conducted. Results: The mean age of the entire population was 68.48 ± 11.53 years. The average LOS was 8.33 ± 5.26 days, with a readmission rate of 73 visits (17.09%) for 56 patients. The NLR (3.79 ± 3.32) showed a low but positive correlation with the LOS (r = 0.222, p < 0.001). Conversely, the PLR (144.84 ± 83.08) did not demonstrate a significant association with the LOS. The NLR presented a low negative correlation for days until the next admission (r = −0.023, p = 0.048). In a prespecified subanalysis of 323 admissions, the NT-proBNP exhibited a low positive Pearson correlation with the NLR (r = 0.241, p < 0.001) and PLR (r = 0.151, p = 0.006). Conclusions: The impact of the NLR across heart failure phenotypes may suggest the role of systemic inflammation in understanding and managing CHF.
Full article
(This article belongs to the Special Issue Diagnosis and Prognosis of Heart Disease, 2nd Edition)
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The Value of C-Reactive Protein and Peritoneal Cytokines as Early Predictors of Anastomotic Leak after Colorectal Surgery
by
Dubravka Mužina, Mario Kopljar, Zdenko Bilić, Blaženka Ladika Davidović, Goran Glavčić, Suzana Janković and Monika Mačkić
Diagnostics 2024, 14(18), 2101; https://doi.org/10.3390/diagnostics14182101 (registering DOI) - 23 Sep 2024
Abstract
Objectives: The aim of this study was to evaluate the accuracy of serum C-reactive protein (CRP) and intraperitoneal CRP, interleukin-6, and tumor necrosis factor-alpha in early diagnostics of anastomotic leakage in the first 4 postoperative days after colorectal surgery. Methods: Between January 2023
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Objectives: The aim of this study was to evaluate the accuracy of serum C-reactive protein (CRP) and intraperitoneal CRP, interleukin-6, and tumor necrosis factor-alpha in early diagnostics of anastomotic leakage in the first 4 postoperative days after colorectal surgery. Methods: Between January 2023 and June 2023, one hundred patients with colorectal carcinoma were operated on with primary anastomosis. Ten patients had anastomotic leak (10%). Results: Based on serum CRP, a patient with a leak will be detected with a 78% probability on postoperative day 3 with values above 169.0 mg/L and on postoperative day 4 with values equal to 159.0 mg/L and above. Intraperitoneal CRP values greater than 56 mg/L on the fourth postoperative day indicate a 78% probability of a diagnosis of leakage. An anastomotic leak will be detected with a 70.0% probability based on an IL-6 value on the first day, at a cut-off value of 42,150. The accuracy of TNF-alpha in predicting anastomotic leak in the first two days is 70% at values higher than 78.00 on the first and 58.50 on the second postoperative day. Conclusion: In this study serum CRP proved to be the most accurate in predicting anastomotic dehiscence after colorectal surgery.
Full article
(This article belongs to the Section Clinical Laboratory Medicine)
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Open AccessReview
Software as a Medical Device (SaMD) in Digestive Healthcare: Regulatory Challenges and Ethical Implications
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Miguel Mascarenhas, Miguel Martins, Tiago Ribeiro, João Afonso, Pedro Cardoso, Francisco Mendes, Hélder Cardoso, Rute Almeida, João Ferreira, João Fonseca and Guilherme Macedo
Diagnostics 2024, 14(18), 2100; https://doi.org/10.3390/diagnostics14182100 (registering DOI) - 23 Sep 2024
Abstract
The growing integration of software in healthcare, particularly the rise of standalone software as a medical device (SaMD), is transforming digestive medicine, a field heavily reliant on medical imaging for both diagnosis and therapeutic interventions. This narrative review aims to explore the impact
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The growing integration of software in healthcare, particularly the rise of standalone software as a medical device (SaMD), is transforming digestive medicine, a field heavily reliant on medical imaging for both diagnosis and therapeutic interventions. This narrative review aims to explore the impact of SaMD on digestive healthcare, focusing on the evolution of these tools and their regulatory and ethical challenges. Our analysis highlights the exponential growth of SaMD in digestive healthcare, driven by the need for precise diagnostic tools and personalized treatment strategies. This rapid advancement, however, necessitates the parallel development of a robust regulatory framework to ensure SaMDs are transparent and deliver universal clinical benefits without the introduction of bias or harm. In addition, the discussion highlights the importance of adherence to the FAIR principles for data management—findability, accessibility, interoperability, and reusability. However, enhanced accessibility and interoperability require rigorous protocols to ensure compliance with data protection guidelines and adequate data security, both of which are crucial for effective integration of SaMDs into clinical workflows. In conclusion, while SaMDs hold significant promise for improving patients’ outcomes in digestive medicine, their successful integration into clinical workflow depends on rigorous data protection protocols and clinical validation. Future directions include the need for adequate clinical and real-world studies to demonstrate that these devices are safe and well-suited to healthcare settings.
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(This article belongs to the Special Issue AI-Driven Diagnostics: Transforming Healthcare from Data to Clinical Decisions)
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Open AccessArticle
RDAG U-Net: An Advanced AI Model for Efficient and Accurate CT Scan Analysis of SARS-CoV-2 Pneumonia Lesions
by
Chih-Hui Lee, Cheng-Tang Pan, Ming-Chan Lee, Chih-Hsuan Wang, Chun-Yung Chang and Yow-Ling Shiue
Diagnostics 2024, 14(18), 2099; https://doi.org/10.3390/diagnostics14182099 (registering DOI) - 23 Sep 2024
Abstract
Background/Objective: This study aims to utilize advanced artificial intelligence (AI) image recog-nition technologies to establish a robust system for identifying features in lung computed tomog-raphy (CT) scans, thereby detecting respiratory infections such as SARS-CoV-2 pneumonia. Spe-cifically, the research focuses on developing a new
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Background/Objective: This study aims to utilize advanced artificial intelligence (AI) image recog-nition technologies to establish a robust system for identifying features in lung computed tomog-raphy (CT) scans, thereby detecting respiratory infections such as SARS-CoV-2 pneumonia. Spe-cifically, the research focuses on developing a new model called Residual-Dense-Attention Gates U-Net (RDAG U-Net) to improve accuracy and efficiency in identification. Methods: This study employed Attention U-Net, Attention Res U-Net, and the newly developed RDAG U-Net model. RDAG U-Net extends the U-Net architecture by incorporating ResBlock and DenseBlock modules in the encoder to retain training parameters and reduce computation time. The training dataset in-cludes 3,520 CT scans from an open database, augmented to 10,560 samples through data en-hancement techniques. The research also focused on optimizing convolutional architectures, image preprocessing, interpolation methods, data management, and extensive fine-tuning of training parameters and neural network modules. Result: The RDAG U-Net model achieved an outstanding accuracy of 93.29% in identifying pulmonary lesions, with a 45% reduction in computation time compared to other models. The study demonstrated that RDAG U-Net performed stably during training and exhibited good generalization capability by evaluating loss values, model-predicted lesion annotations, and validation-epoch curves. Furthermore, using ITK-Snap to convert 2D pre-dictions into 3D lung and lesion segmentation models, the results delineated lesion contours, en-hancing interpretability. Conclusion: The RDAG U-Net model showed significant improvements in accuracy and efficiency in the analysis of CT images for SARS-CoV-2 pneumonia, achieving a 93.29% recognition accuracy and reducing computation time by 45% compared to other models. These results indicate the potential of the RDAG U-Net model in clinical applications, as it can accelerate the detection of pulmonary lesions and effectively enhance diagnostic accuracy. Additionally, the 2D and 3D visualization results allow physicians to understand lesions' morphology and distribution better, strengthening decision support capabilities and providing valuable medical diagnosis and treatment planning tools.
Full article
(This article belongs to the Special Issue Advances in Imaging Diagnosis and Management of Cardiovascular and Pulmonary Diseases)
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Open AccessCase Report
Cleft Sign in MRI May Represent the Disruption of Cartilage Structure within Pubic Symphysis and Pubic Plate: A Cadaver Case Report
by
Haruki Nishimura, Xueqin Gao, Sadao Niga, Naomasa Fukase, Yoichi Murata, Patrick M. Quinn, Masayoshi Saito, Hajime Utsunomiya, Soshi Uchida, Johnny Huard and Marc J. Philippon
Diagnostics 2024, 14(18), 2098; https://doi.org/10.3390/diagnostics14182098 (registering DOI) - 23 Sep 2024
Abstract
Background/Objectives: Long-standing groin pain is a severe issue for athletes, often associated with the cleft sign on magnetic resonance imaging (MRI) scans, yet its underlying causes are poorly understood. The purpose of this study is to histologically examine the pubic plate structure in
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Background/Objectives: Long-standing groin pain is a severe issue for athletes, often associated with the cleft sign on magnetic resonance imaging (MRI) scans, yet its underlying causes are poorly understood. The purpose of this study is to histologically examine the pubic plate structure in cadavers with and without the cleft sign on MRI, shedding light on the pathology behind the cleft sign. Methods: Three fresh human pelvic cadavers underwent 3.0T MRI to detect the cleft sign before histological dissection of pubic plates. Pubic plate tissues were fixed in formalin, decalcified, and processed. Of the two cleft sign-negative specimens, one was cut into sagittal sections, and the other was cut into coronal sections for histology. For the cleft sign positive specimen, a sagittal section was cut. Moreover, 5 µm thick sections were cut at different axial levels for each orientation. Sections were subjected to Safranin O, Alcian blue, and Herovici’s staining or hematoxylin and eosin staining. Results: MRI confirmed that one specimen had a cleft sign in the inferior region on both sides of the pubis and that two specimens had no cleft sign. Both sagittal and coronal sections showed the presence of a cartilage structure continuing from the pubic symphysis to 3 mm laterally within the pubic plate. In the specimen with a positive cleft sign, cartilage damage within the pubic symphysis and pubic plate was identified as revealed by Safranin O staining, Herovici’s staining, and H&E staining. Conclusions: This study elucidated the existence of a cartilage component extending from the pubic symphysis to the pubic plate. The cleft sign in MRI correlated with a disruption in the cartilage component in histology within this specific area.
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(This article belongs to the Section Medical Imaging and Theranostics)
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Open AccessArticle
Early Detection of Lymph Node Metastasis Using Primary Head and Neck Cancer Computed Tomography and Fluorescence Lifetime Imaging
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Nimu Yuan, Mohamed A. Hassan, Katjana Ehrlich, Brent W. Weyers, Garrick Biddle, Vladimir Ivanovic, Osama A. A. Raslan, Dorina Gui, Marianne Abouyared, Arnaud F. Bewley, Andrew C. Birkeland, D. Gregory Farwell, Laura Marcu and Jinyi Qi
Diagnostics 2024, 14(18), 2097; https://doi.org/10.3390/diagnostics14182097 (registering DOI) - 23 Sep 2024
Abstract
Objectives: Early detection and accurate diagnosis of lymph node metastasis (LNM) in head and neck cancer (HNC) are crucial for enhancing patient prognosis and survival rates. Current imaging methods have limitations, necessitating new evaluation of new diagnostic techniques. This study investigates the
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Objectives: Early detection and accurate diagnosis of lymph node metastasis (LNM) in head and neck cancer (HNC) are crucial for enhancing patient prognosis and survival rates. Current imaging methods have limitations, necessitating new evaluation of new diagnostic techniques. This study investigates the potential of combining pre-operative CT and intra-operative fluorescence lifetime imaging (FLIm) to enhance LNM prediction in HNC using primary tumor signatures. Methods: CT and FLIm data were collected from 46 HNC patients. A total of 42 FLIm features and 924 CT radiomic features were extracted from the primary tumor site and fused. A support vector machine (SVM) model with a radial basis function kernel was trained to predict LNM. Hyperparameter tuning was conducted using 10-fold nested cross-validation. Prediction performance was evaluated using balanced accuracy (bACC) and the area under the ROC curve (AUC). Results: The model, leveraging combined CT and FLIm features, demonstrated improved testing accuracy (bACC: 0.71, AUC: 0.79) over the CT-only (bACC: 0.58, AUC: 0.67) and FLIm-only (bACC: 0.61, AUC: 0.72) models. Feature selection identified that a subset of 10 FLIm and 10 CT features provided optimal predictive capability. Feature contribution analysis identified high-pass and low-pass wavelet-filtered CT images as well as Laguerre coefficients from FLIm as key predictors. Conclusions: Combining CT and FLIm of the primary tumor improves the prediction of HNC LNM compared to either modality alone. Significance: This study underscores the potential of combining pre-operative radiomics with intra-operative FLIm for more accurate LNM prediction in HNC, offering promise to enhance patient outcomes.
Full article
(This article belongs to the Special Issue Optimization of Clinical Imaging: From Diagnosis to Prognosis)
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Open AccessReview
Computed Tomography Evaluation of Coronary Atherosclerosis: The Road Travelled, and What Lies Ahead
by
Chadi Ayoub, Isabel G. Scalia, Nandan S. Anavekar, Reza Arsanjani, Clinton E. Jokerst, Benjamin J. W. Chow and Leonard Kritharides
Diagnostics 2024, 14(18), 2096; https://doi.org/10.3390/diagnostics14182096 (registering DOI) - 23 Sep 2024
Abstract
Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to
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Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to support CCTA diagnostic and prognostic value both for stable and acute symptoms. It enables rapid and cost-effective rule-out of CAD, and permits quantification and characterization of coronary plaque and associated significance. In this comprehensive review, we detail the road traveled as CCTA evolved to include quantitative assessment of plaque stenosis and extent, characterization of plaque characteristics including high-risk features, functional assessment including fractional flow reserve-CT (FFR-CT), and CT perfusion techniques. The state of current guideline recommendations and clinical applications are reviewed, as well as future directions in the rapidly advancing field of CT technology, including photon counting and applications of artificial intelligence (AI).
Full article
(This article belongs to the Special Issue Latest Advances and Prospects in Cardiovascular Imaging)
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Open AccessReview
Perioperative Care for Bariatric Surgery
by
Reno Rudiman and Ricarhdo Valentino Hanafi
Diagnostics 2024, 14(18), 2095; https://doi.org/10.3390/diagnostics14182095 (registering DOI) - 23 Sep 2024
Abstract
This review will start with a brief pathophysiology of obesity and the requirement for bariatric surgery, and it continues with a preoperative assessment, which includes a surgical mortality risk assessment, respiratory and cardiovascular assessments, and a psychological assessment. In-hospital postoperative care will be
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This review will start with a brief pathophysiology of obesity and the requirement for bariatric surgery, and it continues with a preoperative assessment, which includes a surgical mortality risk assessment, respiratory and cardiovascular assessments, and a psychological assessment. In-hospital postoperative care will be discussed, including which patients need a surgical intensive care unit and the monitoring tools required. The need for postoperative medications, postoperative complications, strategies for management, and a follow-up plan are also reviewed. This manuscript is written in a narrative review form with a chance of bias as a possible limitation.
Full article
(This article belongs to the Special Issue Diagnosis and Management of Obesity, Eating and Weight-Related Disorders)
Open AccessReview
The Role of Oxidative Stress as a Mechanism in the Pathogenesis of Acute Heart Failure in Acute Kidney Injury
by
Danijela Tasić and Zorica Dimitrijević
Diagnostics 2024, 14(18), 2094; https://doi.org/10.3390/diagnostics14182094 (registering DOI) - 23 Sep 2024
Abstract
Despite a large amount of research on synchronous and mutually induced kidney and heart damage, the basis of the disease is still not fully clarified. Healthy mitochondria are essential for normal kidney and heart function. Mitochondrial dysfunction occurs when the clearance or process
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Despite a large amount of research on synchronous and mutually induced kidney and heart damage, the basis of the disease is still not fully clarified. Healthy mitochondria are essential for normal kidney and heart function. Mitochondrial dysfunction occurs when the clearance or process of generation and fragmentation of mitochondria is disturbed. The kidney is the second organ after the heart in terms of the number of mitochondria. Kidney tubules are rich in mitochondria due to the high energy requirements for absorption of large amounts of ultrafiltrate and dissolved substances. The place of action of oxidative stress is the influence on the balance in the production and breakdown of the mitochondrial reactive oxygen species. A more precise determination of the place and role of key factors that play a role in the onset of the disease is necessary for understanding the nature of the onset of the disease and the creation of therapy in the future. This underscores the urgent need for further research. The narrative review integrates results found in previously performed studies that have evaluated oxidative stress participation in cardiorenal syndrome type 3.
Full article
(This article belongs to the Special Issue Advances in Diagnosis and Management of Urological Diseases)
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An Innovative Hybrid Model for Automatic Detection of White Blood Cells in Clinical Laboratories
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Aziz Aksoy
Diagnostics 2024, 14(18), 2093; https://doi.org/10.3390/diagnostics14182093 (registering DOI) - 22 Sep 2024
Abstract
Background: Microscopic examination of peripheral blood is a standard practice in clinical medicine. Although manual examination is considered the gold standard, it presents several disadvantages, such as interobserver variability, being quite time-consuming, and requiring well-trained professionals. New automatic digital algorithms have been developed
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Background: Microscopic examination of peripheral blood is a standard practice in clinical medicine. Although manual examination is considered the gold standard, it presents several disadvantages, such as interobserver variability, being quite time-consuming, and requiring well-trained professionals. New automatic digital algorithms have been developed to eliminate the disadvantages of manual examination and improve the workload of clinical laboratories. Objectives: Regular analysis of peripheral blood cells and careful interpretation of their results are critical for protecting individual health and early diagnosis of diseases. Because many diseases can occur due to this, this study aims to detect white blood cells automatically. Methods: A hybrid model has been developed for this purpose. In the developed model, feature extraction has been performed with MobileNetV2 and EfficientNetb0 architectures. In the next step, the neighborhood component analysis (NCA) method eliminated unnecessary features in the feature maps so that the model could work faster. Then, different features of the same image were combined, and the extracted features were combined to increase the model’s performance. Results: The optimized feature map was classified into different classifiers in the last step. The proposed model obtained a competitive accuracy value of 95.6%. Conclusions: The results obtained in the proposed model show that the proposed model can be used in the detection of white blood cells.
Full article
(This article belongs to the Special Issue Artificial Intelligence and Deep Learning in Clinical Classification and Prediction)
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The Development of a Yolov8-Based Model for the Measurement of Critical Shoulder Angle (CSA), Lateral Acromion Angle (LAA), and Acromion Index (AI) from Shoulder X-ray Images
by
Turab Selçuk
Diagnostics 2024, 14(18), 2092; https://doi.org/10.3390/diagnostics14182092 (registering DOI) - 22 Sep 2024
Abstract
Background: The accurate and effective evaluation of parameters such as critical shoulder angle, lateral acromion angle, and acromion index from shoulder X-ray images is crucial for identifying pathological changes and assessing disease risk in the shoulder joint. Methods: In this study, a YOLOv8-based
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Background: The accurate and effective evaluation of parameters such as critical shoulder angle, lateral acromion angle, and acromion index from shoulder X-ray images is crucial for identifying pathological changes and assessing disease risk in the shoulder joint. Methods: In this study, a YOLOv8-based model was developed to automatically measure these three parameters together, contributing to the existing literature. Initially, YOLOv8 was used to segment the acromion, glenoid, and humerus regions, after which the CSA, LAA angles, and AI between these regions were calculated. The MURA dataset was employed in this study. Results: Segmentation performance was evaluated with the Dice and Jaccard similarity indices, both exceeding 0.9. Statistical analyses of the measurement performance, including Pearson correlation coefficient, RMSE, and ICC values demonstrated that the proposed model exhibits high consistency and similarity with manual measurements. Conclusions: The results indicate that automatic measurement methods align with manual measurements with high accuracy and offer an effective alternative for clinical applications. This study provides valuable insights for the early diagnosis and management of shoulder diseases and makes a significant contribution to existing measurement methods.
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(This article belongs to the Special Issue Recent Advances in Bone and Joint Imaging—2nd Edition)
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Open AccessArticle
Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics
by
Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea and Cristian Constantin Volovăț
Diagnostics 2024, 14(18), 2091; https://doi.org/10.3390/diagnostics14182091 (registering DOI) - 21 Sep 2024
Abstract
Introduction: Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such
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Introduction: Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such as autoencoders, offer the potential to enhance predictive accuracy. This study aims to evaluate the efficacy of autoencoders compared to traditional ML models in predicting tumor progression or regression after GKRS. Objectives: The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. Methods: This retrospective analysis utilized clinical data from 77 patients treated at the “Prof. Dr. Nicolae Oblu” Emergency Clinic Hospital-Iasi. Twelve variables, including socio-demographic, clinical, treatment, and radiosurgery-related factors, were considered. Tumor progression or regression within three months post-GKRS was the primary outcome, with 71 cases of regression and 6 cases of progression. Traditional ML models, such as Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extra Trees, Random Forest, and XGBoost, were trained and evaluated. The study further explored the impact of incorporating features derived from autoencoders, particularly focusing on the effect of compression in the bottleneck layer on model performance. Results: Traditional ML models achieved accuracy rates ranging from 0.91 (KNN) to 1.00 (Extra Trees). Integrating autoencoder-derived features generally enhanced model performance. Logistic Regression saw an accuracy increase from 0.91 to 0.94, and SVM improved from 0.85 to 0.96. XGBoost maintained consistent performance with an accuracy of 0.94 and an AUC of 0.98, regardless of the feature set used. These results demonstrate that hybrid models combining deep learning and traditional ML techniques can improve predictive accuracy. Conclusions: The study highlights the potential of hybrid models incorporating autoencoder-derived features to enhance the predictive accuracy and robustness of traditional ML models in forecasting tumor dynamics post-GKRS. These advancements could significantly contribute to personalized medicine, enabling more precise and individualized treatment planning based on refined predictive insights, ultimately improving patient outcomes.
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(This article belongs to the Special Issue Integrative Approaches in Head and Neck Cancer Imaging)
Open AccessArticle
Application of the 5th WHO Guidelines for the Diagnosis of Lung Carcinoma in Small Lung Biopsies in a Tertiary Care Center: Is Insecurity of Pathologists for the Accurate Diagnosis Justified?
by
Manuela Beckert, Christian Meyer, Thomas Papadopoulos and Georgia Levidou
Diagnostics 2024, 14(18), 2090; https://doi.org/10.3390/diagnostics14182090 (registering DOI) - 21 Sep 2024
Abstract
Background/Objectives: The diagnosis of lung carcinoma (LC) is currently performed in small biopsies and according to the WHO classification by using limited stains to spare tissue for molecular testing. This procedure, however, often causes diagnostic uncertainty among pathologists. Methods: In this retrospective analysis,
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Background/Objectives: The diagnosis of lung carcinoma (LC) is currently performed in small biopsies and according to the WHO classification by using limited stains to spare tissue for molecular testing. This procedure, however, often causes diagnostic uncertainty among pathologists. Methods: In this retrospective analysis, we compared the diagnosis made by these guidelines in 288 lung biopsies with that using more stains, as retrieved from our archive. We also compared the results of p63 and p40 immunoexpression and investigated the diagnostic role of p53/Rb1. Results: In our investigation, we reached a definite diagnosis with a mean number of one stain compared with six stains in the original diagnostic procedure, with a 97.3% concordance rate. Only in the case of metastases, a clear advantage is proven in the use of more stains, especially in the absence of clinical information. We also found a comparable utility of p40 and p63 for the diagnosis of squamous cell carcinoma, despite the higher p63 expression in other histological types. Moreover, normal p53/Rb1 expression could be utilized for the exclusion of small-cell LC. Conclusions: Our study confirms the diagnostic certainty achieved by the suggestions of the WHO classification and justifies the potential insecurity in the absence of adequate communication with the treating clinician.
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(This article belongs to the Special Issue Histopathology in Cancer Diagnosis and Prognosis)
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Open AccessReview
Review of In Situ Hybridization (ISH) Stain Images Using Computational Techniques
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Zaka Ur Rehman, Mohammad Faizal Ahmad Fauzi, Wan Siti Halimatul Munirah Wan Ahmad, Fazly Salleh Abas, Phaik Leng Cheah, Seow Fan Chiew and Lai-Meng Looi
Diagnostics 2024, 14(18), 2089; https://doi.org/10.3390/diagnostics14182089 (registering DOI) - 21 Sep 2024
Abstract
Recent advancements in medical imaging have greatly enhanced the application of computational techniques in digital pathology, particularly for the classification of breast cancer using in situ hybridization (ISH) imaging. HER2 amplification, a key prognostic marker in 20–25% of breast cancers, can be assessed
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Recent advancements in medical imaging have greatly enhanced the application of computational techniques in digital pathology, particularly for the classification of breast cancer using in situ hybridization (ISH) imaging. HER2 amplification, a key prognostic marker in 20–25% of breast cancers, can be assessed through alterations in gene copy number or protein expression. However, challenges persist due to the heterogeneity of nuclear regions and complexities in cancer biomarker detection. This review examines semi-automated and fully automated computational methods for analyzing ISH images with a focus on HER2 gene amplification. Literature from 1997 to 2023 is analyzed, emphasizing silver-enhanced in situ hybridization (SISH) and its integration with image processing and machine learning techniques. Both conventional machine learning approaches and recent advances in deep learning are compared. The review reveals that automated ISH analysis in combination with bright-field microscopy provides a cost-effective and scalable solution for routine pathology. The integration of deep learning techniques shows promise in improving accuracy over conventional methods, although there are limitations related to data variability and computational demands. Automated ISH analysis can reduce manual labor and increase diagnostic accuracy. Future research should focus on refining these computational methods, particularly in handling the complex nature of HER2 status evaluation, and integrate best practices to further enhance clinical adoption of these techniques.
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(This article belongs to the Special Issue Advances in Machine Learning for Computer-Aided Diagnosis in Biomedical Imaging—2nd Edition)
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Atraumatic Hepatic Laceration with Hemoperitoneum
by
Gaetano Maria Russo, Evangelia Zoi, Imma D’Iglio and Maria Luisa Mangoni di Santo Stefano
Diagnostics 2024, 14(18), 2088; https://doi.org/10.3390/diagnostics14182088 (registering DOI) - 21 Sep 2024
Abstract
Introduction: A rare case of atraumatic liver laceration associated with hemoperitoneum is presented in a patient with amyloidosis who came to the hospital for abdominal pain. Case Presentation: The imaging findings reveal significant hepatomegaly with finely heterogeneous hepatic density and subcapsular hypo-dense streaks
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Introduction: A rare case of atraumatic liver laceration associated with hemoperitoneum is presented in a patient with amyloidosis who came to the hospital for abdominal pain. Case Presentation: The imaging findings reveal significant hepatomegaly with finely heterogeneous hepatic density and subcapsular hypo-dense streaks in segments VI and VII, likely representing lesions. Post-contrast enhancement shows a punctiform contrast medium extravasation within the subhepatic fluid collection, visible from the arterial phase and intensifying in subsequent study phases. Discussion: These imaging findings suggest an atraumatic hepatic laceration, a diagnosis confirmed by the presence of hemoperitoneum distributed bilaterally under the diaphragm, in the paracolic gutters, along the mesentery root, and predominantly in the peri-hepatic region. Conclusion: The detailed imaging analysis provided critical insights into the diagnosis and management of this rare clinical presentation.
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(This article belongs to the Special Issue Diagnosis and Management of Liver Diseases—2nd Edition)
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